scholarly journals Risk Factors for Dementia Incidence Based on Previous Results of the Specific Health Checkups in Japan

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 491
Author(s):  
Yoh Tamaki ◽  
Yoshimune Hiratsuka ◽  
Toshiro Kumakawa
Keyword(s):  
Risk Factors ◽  
Abdominal Circumference ◽  
Multivariable Logistic Regression Analysis ◽  
Common Disease ◽  
Term Care ◽  
Dementia Incidence ◽  
Oral Hypoglycemic Medications ◽  
Larger Sample ◽  
Specific Health

Dementia is a common disease in elderly people, with its prevalence expanding rapidly worldwide. Longitudinal and cohort studies on lifestyle and health conditions are needed to identify the risk of dementia. This study aimed to identify the risk factors for dementia incidence in Japan and to clarify the strategy for its primary care. In this study, an analysis was performed to investigate the association between the cognitive faculty level of the long-term care certification survey and the previous results of the specific health checkups in Japan. To investigate the risk factor for dementia incidence, a multivariable logistic regression analysis was performed, which showed a significant odds ratio for the incidence of dementia for two items, including abdominal circumference and insulin injections or oral hypoglycemic medications. The findings of our study suggested that a lower abdominal circumference had a higher risk for dementia incidence, and individuals who received insulin injections or oral hypoglycemic medications had a higher risk for dementia incidence based on the results of the health checkups conducted 10 years previously. Further, longer duration study with a larger sample is needed to identify the items from the specific health checkups that are associated with the risk of dementia.

Design and Development of a Web-based Delirium Preventive Application for Long-term Care Facilities: A Methodological Study (Preprint)

2020 ◽  
Author(s):  
Kyoung Ja Moon ◽  
Chang-Sik Son ◽  
Jong-Ha Lee ◽  
Mina Park
Keyword(s):  
Risk Factors ◽  
Long Term Care ◽  
Cloud System ◽  
Evidence Based ◽  
Methodological Study ◽  
Term Care ◽  
Web Based ◽  
Care Facilities ◽  
Delirium Prevention

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none

scholarly journals Risk factors for COVID-19 diagnosis, hospitalization, and subsequent all-cause mortality in Sweden: a nationwide study

2021 ◽  
Vol 36 (3) ◽  
pp. 287-298
Author(s):  
Jonathan Bergman ◽  
Marcel Ballin ◽  
Anna Nordström ◽  
Peter Nordström
Keyword(s):  
Risk Factors ◽  
Down Syndrome ◽  
Long Term Care ◽  
Care Facility ◽  
Prescription Medication ◽  
Term Care ◽  
Term Care Facility ◽  
Long Term Care Facility ◽  
All Cause Mortality

AbstractWe conducted a nationwide, registry-based study to investigate the importance of 34 potential risk factors for coronavirus disease 2019 (COVID-19) diagnosis, hospitalization (with or without intensive care unit [ICU] admission), and subsequent all-cause mortality. The study population comprised all COVID-19 cases confirmed in Sweden by mid-September 2020 (68,575 non-hospitalized, 2494 ICU hospitalized, and 13,589 non-ICU hospitalized) and 434,081 randomly sampled general-population controls. Older age was the strongest risk factor for hospitalization, although the odds of ICU hospitalization decreased after 60–69 years and, after controlling for other risk factors, the odds of non-ICU hospitalization showed no trend after 40–49 years. Residence in a long-term care facility was associated with non-ICU hospitalization. Male sex and the presence of at least one investigated comorbidity or prescription medication were associated with both ICU and non-ICU hospitalization. Three comorbidities associated with both ICU and non-ICU hospitalization were asthma, hypertension, and Down syndrome. History of cancer was not associated with COVID-19 hospitalization, but cancer in the past year was associated with non-ICU hospitalization, after controlling for other risk factors. Cardiovascular disease was weakly associated with non-ICU hospitalization for COVID-19, but not with ICU hospitalization, after adjustment for other risk factors. Excess mortality was observed in both hospitalized and non-hospitalized COVID-19 cases. These results confirm that severe COVID-19 is related to age, sex, and comorbidity in general. The study provides new evidence that hypertension, asthma, Down syndrome, and residence in a long-term care facility are associated with severe COVID-19.

Incidence and risk factors of hospital falls on long-term care wards in Japan

2011 ◽  
Vol 18 (3) ◽  
pp. 572-577 ◽  
Author(s):  
Buichi Tanaka ◽  
Mio Sakuma ◽  
Masae Ohtani ◽  
Jinichi Toshiro ◽  
Tadashi Matsumura ◽  
...  
Keyword(s):  
Risk Factors ◽  
Long Term Care ◽  
Term Care

scholarly journals Case–control study to estimate odds of death within 28 days of positive test for SARS-CoV-2 prior to vaccination for residents of long-term care facilities in England, 2020–2021

2021 ◽  
pp. jech-2021-218135
Author(s):  
Karthik Paranthaman ◽  
Hester Allen ◽  
Dimple Chudasama ◽  
Neville Q Verlander ◽  
James Sedgwick
Keyword(s):  
Long Term Care ◽  
Multivariable Analysis ◽  
Adverse Outcomes ◽  
Positive Test ◽  
Mortality Data ◽  
Multivariable Logistic Regression Analysis ◽  
Term Care ◽  
Increased Risk ◽  
Care Facilities

BackgroundPersons living in long-term care facilities (LTCFs) are presumed to be at higher risk of adverse outcomes from SARS-CoV-2 infection due to increasing age and frailty, but the magnitude of increased risk is not well quantified.MethodsAfter linking demographic and mortality data for cases with confirmed SARS-CoV-2 infection between March 2020 and January 2021 in England, a random sample of 6000 persons who died and 36 000 who did not die within 28 days of a positive test was obtained from the dataset of 3 020 800 patients. Based on an address-matching process, the residence type of each case was categorised into one of private home and residential or nursing LTCF. Univariable and multivariable logistic regression analysis was conducted.ResultsMultivariable analysis showed that an interaction effect between age and residence type determined the outcome. Compared with a 60-year-old person not living in LTCF, the adjusted OR (aOR) for same-aged persons living in residential and nursing LTCFs was 1.77 (95% CI 1.21 to 2.6, p=0.0017) and 3.95 (95% CI 2.77 to 5.64, p<0.0001), respectively. At 90 years of age, aORs were 0.87 (95% CI 0.72 to 1.06, p=0.21) and 0.74 (95% CI 0.61 to 0.9, p=0.001), respectively. The model had an overall accuracy of 94.2% (94.2%) when applied to the full dataset of 2 978 800 patients.ConclusionThis study found that residents of LTCFs in England had higher odds of death up to 80 years of age. Beyond 80 years, there was no difference in the odds of death for LTCF residents compared with those in the wider community.

Risk Factors for Depression in Long-Term Care: A Systematic Review

2018 ◽  
Vol 42 (3) ◽  
pp. 224-237 ◽  
Author(s):  
Rebecca Chau ◽  
David W. Kissane ◽  
Tanya E. Davison
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Long Term Care ◽  
Term Care

Risk factors for fecal carriage of IMP-6-producing Enterobacteriaceae at a long-term care hospital in Japan: A follow-up report from the northern Osaka multicentre study group

2018 ◽  
Vol 24 (9) ◽  
pp. 769-772 ◽  
Author(s):  
Hideharu Hagiya ◽  
Norihisa Yamamoto ◽  
Ryuji Kawahara ◽  
Yukihiro Akeda ◽  
Rathina Kumar Shanmugakani ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multicentre Study ◽  
Long Term Care ◽  
Study Group ◽  
Care Hospital ◽  
Term Care ◽  
Fecal Carriage

scholarly journals Risk factors for pneumonia and influenza hospitalizations in long-term care facility residents: a retrospective cohort study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Patience Moyo ◽  
Andrew R. Zullo ◽  
Kevin W. McConeghy ◽  
Elliott Bosco ◽  
Robertus van Aalst ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Long Term Care ◽  
Care Facility ◽  
Term Care ◽  
Term Care Facility ◽  
Long Term Care Facility

Comparing Changes and Transitions of Home Care Clients in Retirement Homes and Private Homes

2019 ◽  
Vol 39 (3) ◽  
pp. 421-431
Author(s):  
Jeffrey Poss ◽  
Chi-Ling Sinn ◽  
Galina Grinchenko ◽  
Lialoma Salam-White ◽  
John Hirdes
Keyword(s):  
Risk Factors ◽  
Home Care ◽  
Long Term Care ◽  
Local Health ◽  
Caregiver Distress ◽  
Retirement Home ◽  
Term Care ◽  
Home Residency ◽  
Private Homes

ABSTRACTLong-stay home care clients mostly reside in private homes or retirement homes, and the type of residence may influence risk factors for long-term care placement. This multi-state analytic study uses RAI-Home Care and administrative data from the Hamilton Niagara Haldimand Brant Local Health Integration Network to model conceptualized states of risk at baseline through a 13-month follow-up period. Modifiable risk factors in these states were client loneliness or depressive symptoms, and caregiver distress. A higher adjusted likelihood of being discharged deceased was found for the lowest-risk clients in retirement homes. Adjusting for client, service, and caregiver characteristics, retirement home residency was associated with higher likelihood of placement in a long-term care home; reduced caregiver distress; and increased client loneliness/depression. As an alternative to private home settings as the location for aging in place among these long-stay home care clients, retirement home residency represents some trade-offs between client and informal caregiver.

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